Aviz Networks Blogs

Many hackers are able to breach various parts of the healthcare system because the SecOps team is unable to quickly understand how far an attacker can spread throughout multiple systems. Hospitals, clinics, telemedicine, cloud services, devices and facility systems create traffic on a common network; however, due to lack of central control over how traffic flows & devices in the Silverado system, many of these facilities have blind spots pertaining to the analysis of East to West traffic, devices that are not monitored (unmanaged) & mixed infrastructure (devices that do not have agent-based security monitoring). Some examples of this are: Almost all types of ransomware operated by transferring themselves around to other locations before they perform file&folder encryptions. A lot of the different device types and workloads out there within the Healthcare ecosystem will not be able to utilize endpoint agents. Packet level evidence will assist with identifying unusual flows o...

In today's world of healthcare, thousands of connected devices rely on one another, such as infusion pumps, imaging equipment, badge readers, controllers of H/VAC, clinical stations and tele-health endpoints. A majority of these types of devices do not support security agents, can't be patched and were not designed with cybersecurity in mind; they were simply designed to provide safe reliable clinical care.  Here are some real-world observations related to the above statement: • There are substantial amounts of valuable traffic signals that are generated on connected medial and facility devices • Many of the devices cannot be secured by the use of traditional endpoint controls • Packet-level visibility can provide insight into device behaviour patterns, communications, and risk • Optimized delivery of traffic helps improve the accuracy of asset discovery and monitoring tools • Network evidence can support security compliance and incident investigation processes There is a comm...

AI factories have already introduced a completely new way of thinking regarding networking. Network used to serve the purpose of connecting devices. Nowadays, it influences the performance of workload execution, the level of isolation, usage of GPU, troubleshooting speeds, etc. It has become possible to validate the operational processes by creating a digital twin environment before any changes get implemented. By doing that, it would be possible to test AI fabrics, topology configuration options, create tenants, telemetry gathering, and much more within the environment. It is important not to forget about switching from automated deployment and management to intelligent operations. It will be possible to analyze alarms, find reasons for network congestion, detect drifts in configuration, examine telemetry information, generate health summaries, and so on. In other words, there won't be such a need to use multiple dashboards and CLI configurations. To sum up, an AI-friendly network...

PCI-DSS 4.0 raises the bar for financial services organisations by making compliance more evidence-driven. Institutions now need to show ongoing proof for encryption in transit, certificate validity, user activity, network monitoring, insecure protocols, malware signals, and risk analysis across complex environments. This is difficult because financial traffic no longer stays inside one controlled data center. It moves across hybrid cloud, APIs, branches, partners, payment systems, and internal workloads. Application logs and endpoint telemetry are useful, but they often depend on the health and honesty of the system generating them. During failures or attacks, that evidence can become incomplete. Packet-derived evidence helps close this visibility gap by observing traffic independently at the network layer. It can show which protocols are being used, which TLS sessions are active, what certificates are present, which DNS queries are occurring, which web transactions are visible, and ...

AI factories have already introduced a completely new way of thinking regarding networking. Network used to serve the purpose of connecting devices. Nowadays, it influences the performance of workload execution, the level of isolation, usage of GPU, troubleshooting speeds, etc. It has become possible to validate the operational processes by creating a digital twin environment before any changes get implemented. By doing that, it would be possible to test AI fabrics, topology configuration options, create tenants, telemetry gathering, and much more within the environment. It is important not to forget about switching from automated deployment and management to intelligent operations. It will be possible to analyze alarms, find reasons for network congestion, detect drifts in configuration, examine telemetry information, generate health summaries, and so on. In other words, there won't be such a need to use multiple dashboards and CLI configurations. To sum up, an AI-friendly network...

IT departments in the public sector are under tremendous pressure to support cloud computing, cyber security, hybrid work, and AI solutions while adhering to shoestring budgets. An event in the industry revealed that using open networking helps make government networks adaptable and affordable. The key lesson? Avoid vendor lock-ins. With open networking based on standards, it is much easier for an organization to introduce new technology to its network without getting entangled with any hardware or software requirements. A solution to these concerns would be the deployment of artificial intelligence in the operations process. Instead of adding yet more technology and more people, intelligent observability makes the best use of what you have by converting alerts to information, accelerating issue resolution, and enabling multi-vendor environments to work effectively. The take away from all of this for county IT leaders would be that network modernization does not necessarily need to cos...